Throughout this application various publications are referred to in parenthesis. Full citations for these references may be found at the end of the specification immediately preceding the claims. The disclosures of these publications are hereby incorporated by reference in their entireties into the subject application to more fully describe the art to which the subject application pertains.
Magnetic resonance imaging (MRI) is widely used in clinical diagnosis. In an MRI imaging sequence, a uniform magnetic field B0 is applied to an imaged object along the z-axis of a spatial Cartesian reference frame. The effect of the magnetic field B0 is to align some of the object's nuclear spins along the z-axis. In such a field, the nuclei resonate at their Larmor frequencies according to the following equation:ω=γB0 where ω is the Larmor frequency, and γ is the gyromagnetic ratio. The gyromagnetic ratio is constant and a property of the particular nucleus. The protons of water, for example, because of their relative abundance in biological tissue are of interest in MRI imaging. The value of the gyromagnetic ratio γ for the protons of water is about 4.26 kHz/Gauss. Therefore, in a 1.5 Tesla polarizing magnetic field B0, the resonance or Larmor frequency of the protons is approximately 63.9 MHz.
Materials other than water, principally lipids, may also be found in biological tissue. The protons of lipids have a slightly different gyromagnetic ratio; the lipid frequency is approximately 220 Hz lower than that of water protons in the same 1.5 Tesla polarizing magnetic field B0. The difference between the Larmor frequencies of such different substances, under an identical magnetic polarizing field is termed “chemical shift” and is designated by the term Δv. Accordingly, Δv increases as the field strength B0 increases.
The accuracy of an MRI image is highly dependent upon the uniformity of the polarizing magnetic field B0. Ordinary variations in the magnetic field may be due to structural asymmetries in the MRI coil itself, and tend to be relatively static and predictable, and therefore easier to compensate. For example, it is well known in the art that the homogeneity of the polarizing magnetic field B0 may be improved by shim coils which are oriented to selectively produce a magnetic field that interacts with B0 in a manner that offsets known inhomogeneity in the field. However, the object being imaged also has a significant effect on magnetic field homogeneity which can be more difficult to detect and correct. Furthermore, the ability of shim coils to correct even accurately and precisely known inhomogeneity is limited by the number and geometry of the shim coils available.
For MRI imaging of the brain, a variety of automated non-iterative shimming methods using either columnar projections (1-5) or images of phase evolution to generate B0 maps have been reported (6-11). Intrinsic to most of these methods is the assumption that there is only a single chemical species contributing to the image. Under these conditions the frequency offset (i.e., B0 inhomogeneity) can be determined from the phase difference between two acquisitions acquired with different evolution times. However in organs and tissues outside of the brain the lipid resonances can dominate the water resonance. For example, in skeletal muscle, lipid contributions from skin, bone marrow and structural fat exceed the water resonance. When significant lipid contributions are present, the measured phase reflects a vector sum of water and lipid resonances, with the phase of the lipid resonances being modulated by both the intrinsic field inhomogeneity and the chemical shift difference between the water and lipid resonances. In these instances, standard phase difference based B0 mapping methods using arbitrary evolution times cannot be used due to the additional phase/frequency contribution arising from the lipid resonances (9).
To address this problem for the whole head, including both brain and scalp, Schneider and Glover (9) reported that the lipid artifact from the scalp in brain B0 maps could be reduced if the evolution time Δt was chosen such that the phase precession due to the chemical shift of the methylene lipid resonance was exactly 2π relative to that of water. Thus, at this evolution time, resolution of the fat and water resonances and correction for the additional phase precession of the fat resonance is not required (12). However, the use of a single relatively short time interval limits the accuracy of the B0 maps obtained (2). Similarly, the maximum frequency span measurable without aliasing is also limited. This becomes especially acute at higher field strengths as Δν increases (1/Δν<2 ms at 4 T).
Although integral multiples of 1/Δν can be used to increase the accuracy, this increases the probability that aliasing will occur and the severity of any aliasing that does occur. Although sophisticated mathematical algorithms for phase unwrapping in two (13) and three dimensions (14) have been described, they are based on assumptions regarding the rate of change in B0 and dB0/dr, which may not hold in regions of high local susceptibility. These inaccuracies then result in errors in the calculated shims, necessitating additional iterations or in some cases incorrect solutions. Thus, spectroscopic imaging studies outside the brain, which sample large regions of interest (ROIs), continue to be limited by the inability to simultaneously shim large regions automatically (15).
In the brain where lipids are not an issue, the limitation in accuracy and aliasing have been overcome by using a multi-evolution time acquisition with a novel acquisition based unwrapping scheme that makes no assumptions regarding dB0/dr, providing both high accuracy and high bandwidth (large ΔB0 range) (10, 11). However, to be applicable outside of the brain, the effects of additional phase precession of the lipid signal due to chemical shift evolution must be deconvoluted from phase precession in both resonances due to B0 inhomogeneity.
As originally described by Dixon (16), water and fat can be resolved from each other in images using the differential phase modulation of the lipid resonance due to chemical shift difference with water when two images are added/subtracted and an additional evolution time (Δt=½Δν) is used in the second image. As noted by Glover and colleagues (17), the performance of this approach degrades in the presence of B0 inhomogeneity, since phase modulation due to chemical shift differences cannot be resolved from inhomogeneity in the main field. To overcome this effect, various three point measurement methods have been described (18, 19). These measurements allow the content of fat and water to be identified independent of the B0 inhomogeneity present, under the conditions that the dominant species could be identified.
Although Dixon imaging is effective at distinguishing between water and lipid resonances, Dixon images do not themselves provide an accurate map of B0 inhomogeneity. Accordingly, a need exists for a method for generating an accurate B0 map in the presence of an object having two materials having different Larmor frequencies. In particular, a need exists for a non-iterative method for mapping B0 inhomogeneity in the presence of high lipid levels relative to water, for example as in the human leg.